Out[78]:
Quick recap of Fourier Transformation¶
X time points: 1000 Duration: 10.0 s Sampling rate: 100.0Hz Nyquist frequency: 50.0Hz Signal frequency of 2Hz X samples: 1000 1000 calculated fourier points 1000 calculated fourier frequency points
Out[9]:
Text(0.5, 0, 'Hz')
Read in raw data¶
The data used for this analysis are 1second power measurements on park level of the offshore wind farms:
- Mermaid (28WTG, 8.4MW per WTG, 235MW capacity in total)
- Seastar (30WTG, 8.4MW per WTG, 252MW capacity in total)
- Rentel (42 WTG, 7.35MW per WTG, 309MW capacity in total)
The time period is from 2 November until 28 November.
Rentel 2021120_COMP_Rentel - 20.11.2021 - 27.11.2021_e743_20_11_21_01_00_00_High resolution parameters 1 Second.csv Seastar 20111101_COMP_Seastar - 01.11.2021 - 09.11.2021_5ca9_01_11_21_01_00_00_High resolution parameters 1 Second(1).csv Mermaid - 20211120_COMP_Mermaid - 20.11.2021 - 28.11.2021_2def_20_11_21_01_00_00_High resolution parameters 1 Second.csv Rentel 20211110_COMP_Rentel - 10.11.2021 - 19.11.2021_14ce_10_11_21_01_00_00_High resolution parameters 1 Second.csv Mermaid 20211102_COMP_Mermaid - 02.11.2021 - 9.11.2021_d131_01_11_21_01_00_00_High resolution parameters 1 Second.csv Seastar 20111120_COMP_Seastar - 20.11.2021 - 28.11.2021_e1bc_20_11_21_01_00_00_High resolution parameters 1 Second(1).csv Mermaid 20211110_COMP_Mermaid - 10.11.2021 - 20.11.2021_0661_10_11_21_01_00_00_High resolution parameters 1 Second.csv Seastar 20111110_COMP_Seastar - 10.11.2021 - 19.11.2021_c5fb_10_11_21_13_00_00_High resolution parameters 1 Second(1).csv Rentel 20211101_COMP_Rentel - 1.11.2021 - 09.11.2021_a9bb_01_11_21_13_00_00_High resolution parameters 1 Second.csv Read in 2275229 lines of Mermaid data Read in 2365222 lines of Seastar data Read in 2336408 lines of Rentel data
0.0% of lines in Mermaid data is null 0.0% of lines in Seastar data is null 0.0% of lines in Rentel data is null
Out[20]:
| mermaid_active_power | seastar_active_power | rentel_active_power | |
|---|---|---|---|
| datetime | |||
| 2021-11-23 07:13:22 | 60.001780 | 47.989970 | 35.271730 |
| 2021-11-28 02:47:29 | 222.677800 | 238.551200 | 295.145200 |
| 2021-11-08 18:12:36 | 0.127204 | 2.834981 | 0.765502 |
| 2021-11-25 03:12:58 | 55.626260 | 44.259790 | 56.583370 |
| 2021-11-07 02:47:11 | 228.979800 | 232.613100 | 289.750700 |
Out[140]:
<seaborn.axisgrid.PairGrid at 0x7fcc25e37be0>
Fourier transformation complete time period¶
A first very rough analysis to investigate the nature of the problem. A simple fourier transformation of the complete time period is made, and the maximum frequency between 0,2Hz and 0,3Hz is calculated for each windfarm individually and the total of the three windfarms combined.
Out[141]:
| mermaid_active_power | seastar_active_power | rentel_active_power | total_active_power | |
|---|---|---|---|---|
| datetime | ||||
| 2021-11-02 14:00:00 | 13.38953 | 13.88150 | 20.03320 | 47.30423 |
| 2021-11-02 14:00:01 | 13.45399 | 14.09939 | 19.93910 | 47.49248 |
| 2021-11-02 14:00:01 | 13.45399 | 14.09939 | 20.12528 | 47.67866 |
| 2021-11-02 14:00:02 | 13.30142 | 14.13340 | 20.20849 | 47.64331 |
| 2021-11-02 14:00:03 | 13.08963 | 13.99785 | 20.22351 | 47.31099 |
Sampling frequency = 1.02Hz
Function to apply Butterworth filter to a shorter time bin¶
The function does the following with a time series:
- Verify that the timeseries is consequtive, or in other words, that there are no time gaps
- Apply the second order bandpass butterworth filter, with lowpass frequency 0,15Hz and highpass frequency 0,3Hz.
- Calculate and return the average power of the absolute values of the filtered signal
- Make a plot if requested
Apply the filter to 10.000 random short term time periods¶
We can now apply the applyButterWorth function to 10.000 random time periods. We will apply the filter to all 3 windfarms + the total of the tree windfarms.
You can choose the length of this time period.
Calculating parameters of random window 0 Calculating parameters of random window 100 Calculating parameters of random window 200 Calculating parameters of random window 300 Calculating parameters of random window 400 Calculating parameters of random window 500 Calculating parameters of random window 600 Calculating parameters of random window 700 Calculating parameters of random window 800 Calculating parameters of random window 900 Calculating parameters of random window 1000 Calculating parameters of random window 1100 Calculating parameters of random window 1200 Calculating parameters of random window 1300 Calculating parameters of random window 1400 Calculating parameters of random window 1500 Calculating parameters of random window 1600 Calculating parameters of random window 1700 Calculating parameters of random window 1800 Calculating parameters of random window 1900 Calculating parameters of random window 2000 Calculating parameters of random window 2100 Calculating parameters of random window 2200 Calculating parameters of random window 2300 Calculating parameters of random window 2400 Calculating parameters of random window 2500 Calculating parameters of random window 2600 Calculating parameters of random window 2700 Calculating parameters of random window 2800 Calculating parameters of random window 2900 Calculating parameters of random window 3000 Calculating parameters of random window 3100 Calculating parameters of random window 3200 Calculating parameters of random window 3300 Calculating parameters of random window 3400 Calculating parameters of random window 3500 Calculating parameters of random window 3600 Calculating parameters of random window 3700 Calculating parameters of random window 3800 Calculating parameters of random window 3900 Calculating parameters of random window 4000 Calculating parameters of random window 4100 Calculating parameters of random window 4200 Calculating parameters of random window 4300 Calculating parameters of random window 4400 Calculating parameters of random window 4500 Calculating parameters of random window 4600 Calculating parameters of random window 4700 Calculating parameters of random window 4800 Calculating parameters of random window 4900 Calculating parameters of random window 5000 Calculating parameters of random window 5100 Calculating parameters of random window 5200 Calculating parameters of random window 5300 Calculating parameters of random window 5400 Calculating parameters of random window 5500 Calculating parameters of random window 5600 Calculating parameters of random window 5700 Calculating parameters of random window 5800 Calculating parameters of random window 5900 Calculating parameters of random window 6000 Calculating parameters of random window 6100 Calculating parameters of random window 6200 Calculating parameters of random window 6300 Calculating parameters of random window 6400 Calculating parameters of random window 6500 Calculating parameters of random window 6600 Calculating parameters of random window 6700 Calculating parameters of random window 6800 Calculating parameters of random window 6900 Calculating parameters of random window 7000 Calculating parameters of random window 7100 Calculating parameters of random window 7200 Calculating parameters of random window 7300 Calculating parameters of random window 7400 Calculating parameters of random window 7500 Calculating parameters of random window 7600 Calculating parameters of random window 7700 Calculating parameters of random window 7800 Calculating parameters of random window 7900 Calculating parameters of random window 8000 Calculating parameters of random window 8100 Calculating parameters of random window 8200 Calculating parameters of random window 8300 Calculating parameters of random window 8400 Calculating parameters of random window 8500 Calculating parameters of random window 8600 Calculating parameters of random window 8700 Calculating parameters of random window 8800 Calculating parameters of random window 8900 Calculating parameters of random window 9000 Calculating parameters of random window 9100 Calculating parameters of random window 9200 Calculating parameters of random window 9300 Calculating parameters of random window 9400 Calculating parameters of random window 9500 Calculating parameters of random window 9600 Calculating parameters of random window 9700 Calculating parameters of random window 9800 Calculating parameters of random window 9900
Analyse the results¶
- Drop time periods in which there were time gaps
- Drop time periods in which the power output was below 0MW
Start with 10000 time bins 8683 time bins left after removal of time gaps and negative powers
Out[963]:
| timeseries_test | total_mean_power | intial_time | total_mean_amplitude_filtered_signal | total_mean_amplitude_filtered_signal_relative | mermaid_mean_power | mermaid_mean_amplitude_filtered_signal | mermaid_mean_amplitude_filtered_signal_relative | seastar_mean_power | seastar_mean_amplitude_filtered_signal | seastar_mean_amplitude_filtered_signal_relative | rentel_mean_power | rentel_mean_amplitude_filtered_signal | rentel_mean_amplitude_filtered_signal_relative | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3468 | OK | 740.331763 | 2021-11-22 02:38:23 | 0.439188 | 0.059323 | 219.557835 | 0.248282 | 0.113083 | 237.235525 | 0.307475 | 0.129607 | 283.538402 | 0.195216 | 0.06885 |
Out[967]:
| percentile | mermaid_mean_amplitude [MW] | seastar_mean_amplitude [MW] | rentel_mean_amplitude [MW] | total_mean_amplitude [MW] | |
|---|---|---|---|---|---|
| 0 | 1 | 0.050936 | 0.043797 | 0.012868 | 0.077641 |
| 1 | 5 | 0.073217 | 0.061764 | 0.020323 | 0.105621 |
| 2 | 25 | 0.146866 | 0.125512 | 0.038818 | 0.203881 |
| 3 | 50 | 0.236496 | 0.211318 | 0.069362 | 0.343721 |
| 4 | 75 | 0.346174 | 0.318443 | 0.172275 | 0.503083 |
| 5 | 95 | 0.536592 | 0.498786 | 0.336292 | 0.774633 |
| 6 | 99 | 0.691233 | 0.645395 | 0.458974 | 1.002761 |
Out[968]:
| percentile | mermaid_mean_relative_amplitude [%] | seastar_mean_relative_amplitude [%] | rentel_mean_relative_amplitude [%] | total_mean_relative_amplitude [%] | |
|---|---|---|---|---|---|
| 0 | 1 | 0.070466 | 0.068022 | 0.034266 | 0.038397 |
| 1 | 5 | 0.099994 | 0.095816 | 0.045876 | 0.051709 |
| 2 | 25 | 0.171645 | 0.170434 | 0.072085 | 0.087370 |
| 3 | 50 | 0.276894 | 0.290283 | 0.102209 | 0.141296 |
| 4 | 75 | 0.540163 | 0.581798 | 0.163145 | 0.266312 |
| 5 | 95 | 2.911684 | 2.222262 | 0.884562 | 0.946097 |
| 6 | 99 | 9.277767 | 5.737267 | 3.022734 | 2.170056 |
Read in turbine data¶
2021-11-20 00:00:01 2021-11-28 23:59:58
2021-11-20 00:00:00 2021-11-28 23:59:58
2021-11-20 00:00:00 2021-11-28 23:59:58
2021-11-20 00:00:02 2021-11-28 23:59:33
Out[705]:
| MA1_nacelle_dir | SA1_nacelle_dir | R_A1_nacelle_dir | MA1_rpm | SA1_rpm | R_A1_rpm | MA1_forcey | SA1_forcey | MA1_forcex | SA1_forcex | |
|---|---|---|---|---|---|---|---|---|---|---|
| datetime | ||||||||||
| 2021-11-20 00:00:00 | NaN | NaN | NaN | NaN | NaN | NaN | -0.04 | 0.02 | -0.04 | -0.05 |
| 2021-11-20 00:00:01 | NaN | NaN | NaN | NaN | NaN | 4.0 | 0.01 | 0.13 | -0.03 | -0.09 |
| 2021-11-20 00:00:02 | NaN | NaN | 264.750 | NaN | NaN | 4.0 | 0.04 | 0.01 | 0.03 | 0.03 |
| 2021-11-20 00:00:03 | NaN | NaN | 264.375 | NaN | NaN | 4.0 | 0.00 | -0.11 | NaN | 0.09 |
| 2021-11-20 00:00:04 | NaN | NaN | 264.000 | NaN | NaN | 4.0 | -0.03 | -0.03 | -0.01 | 0.00 |
Look at correlations Mermaid turbine data and tower osscillations¶
Out[738]:
| MA1_nacelle_dir | MA1_rpm | MA1_forcey | MA1_forcex | |
|---|---|---|---|---|
| datetime | ||||
| 2021-11-20 00:11:06 | NaN | 4.02 | 0.03 | NaN |
| 2021-11-20 00:11:09 | 260.736330 | 4.23 | 0.03 | -0.02 |
| 2021-11-20 00:11:11 | 260.753908 | 4.45 | -0.03 | 0.02 |
| 2021-11-20 00:11:13 | 260.771486 | 4.68 | 0.00 | -0.01 |
| 2021-11-20 00:11:15 | 260.789064 | 4.93 | 0.01 | 0.01 |
Out[754]:
| MA1_nacelle_dir | MA1_rpm | MA1_forcey | MA1_forcex | |
|---|---|---|---|---|
| datetime | ||||
| 2021-11-21 04:12:53 | 345.187575 | 6.14 | NaN | 0.18 |
| 2021-11-22 23:20:01 | 26.727540 | 7.60 | 0.02 | 0.08 |
| 2021-11-28 04:15:11 | 12.818787 | 10.97 | -0.11 | 0.15 |
| 2021-11-28 18:58:33 | 349.000000 | 10.09 | -0.09 | 0.20 |
| 2021-11-22 19:41:53 | 43.328527 | 6.79 | -0.16 | -0.06 |
Start with 479 time bins
Out[755]:
| timeseries_test | mermaid_mean_power | mermaid_mean_amplitude_filtered_signal | mermaid_mean_amplitude_filtered_signal_relative | |
|---|---|---|---|---|
| datetime | ||||
| 2021-11-21 04:12:53 | OK | 118.380214 | 0.393791 | 0.332649 |
| 2021-11-22 23:20:01 | OK | 35.027761 | 0.241087 | 0.688274 |
| 2021-11-28 04:15:11 | OK | 225.342346 | 0.439175 | 0.194893 |
| 2021-11-22 19:41:53 | OK | 98.746027 | 0.235073 | 0.238058 |
| 2021-11-22 15:20:37 | OK | 105.794718 | 0.406257 | 0.384005 |
Out[756]:
| MA1_nacelle_dir | MA1_rpm | MA1_forcey | MA1_forcex | |
|---|---|---|---|---|
| datetime | ||||
| 2021-11-21 04:12:53 | 345.187575 | 6.14 | NaN | 0.18 |
| 2021-11-22 23:20:01 | 26.727540 | 7.60 | 0.02 | 0.08 |
| 2021-11-28 04:15:11 | 12.818787 | 10.97 | -0.11 | 0.15 |
| 2021-11-28 18:58:33 | 349.000000 | 10.09 | -0.09 | 0.20 |
| 2021-11-22 19:41:53 | 43.328527 | 6.79 | -0.16 | -0.06 |
Out[758]:
| MA1_nacelle_dir | MA1_rpm | MA1_forcey | MA1_forcex | timeseries_test | mermaid_mean_power | mermaid_mean_amplitude_filtered_signal | mermaid_mean_amplitude_filtered_signal_relative | |
|---|---|---|---|---|---|---|---|---|
| datetime | ||||||||
| 2021-11-20 02:05:03 | 227.669780 | 6.03 | 0.10 | 0.01 | OK | 17.064669 | 0.115400 | 0.676250 |
| 2021-11-20 04:54:31 | 248.976802 | 6.68 | -0.04 | -0.01 | OK | 25.999292 | 0.106157 | 0.408308 |
| 2021-11-20 05:07:18 | 251.415927 | 6.03 | -0.05 | 0.00 | OK | 27.324399 | 0.093956 | 0.343855 |
| 2021-11-20 05:21:34 | 251.687110 | 6.22 | -0.04 | 0.02 | OK | 25.331451 | 0.099454 | 0.392609 |
| 2021-11-20 07:04:15 | 253.641700 | 6.78 | -0.04 | 0.03 | OK | 44.647854 | 0.092173 | 0.206445 |
Out[779]:
<seaborn.axisgrid.PairGrid at 0x7fcba5fe3390>
Read in OSS 15 minute meteo files¶
MER_wind_dir SEA_wind_dir RTL_wind_dir
datetime
2021-11-20 00:00:00 256.548459 253.875275 253.761067
2021-11-20 00:15:00 255.751532 246.845170 244.925881
2021-11-20 00:30:00 256.179482 247.987775 240.254692
2021-11-20 00:45:00 250.501580 253.723330 240.381055
2021-11-20 01:00:00 245.495300 250.678891 235.531103
MER_wind_speed SEA_wind_speed RTL_wind_speed
datetime
2021-11-20 00:00:00 3.729670 3.208010 3.932496
2021-11-20 00:15:00 3.335881 3.450055 3.918132
2021-11-20 00:30:00 3.824412 3.793800 3.866130
2021-11-20 00:45:00 4.195291 3.805244 3.857697
2021-11-20 01:00:00 4.660578 4.256435 4.361534
MER_wave_dir SEA_wave_dir
datetime
2021-11-20 00:00:00 341.13 309.22
2021-11-20 00:15:00 339.60 334.23
2021-11-20 00:30:00 355.10 343.71
2021-11-20 00:45:00 358.99 334.77
2021-11-20 01:00:00 370.04 346.31
MER_wave_height SEA_wave_height RTL_wave_height
datetime
2021-11-20 00:00:00 0.5843 0.5368 0.5612
2021-11-20 00:15:00 0.5787 0.5445 0.5653
2021-11-20 00:30:00 0.5889 0.5494 0.5614
2021-11-20 00:45:00 0.5512 0.5456 0.5525
2021-11-20 01:00:00 0.5625 0.5382 0.5225
MER_wave_period SEA_wave_period RTL_wave_period
datetime
2021-11-20 00:00:00 4.87 4.73 5.08
2021-11-20 00:15:00 4.75 5.08 5.21
2021-11-20 00:30:00 5.36 4.81 5.25
2021-11-20 00:45:00 5.22 5.20 4.94
2021-11-20 01:00:00 5.27 5.21 5.04
Out[1053]:
| MER_wave_dir | SEA_wave_dir | MER_wave_height | SEA_wave_height | RTL_wave_height | MER_wave_period | SEA_wave_period | RTL_wave_period | MER_wind_dir | SEA_wind_dir | RTL_wind_dir | MER_wind_speed | SEA_wind_speed | RTL_wind_speed | MER_wind_wave_misalignment | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| datetime | |||||||||||||||
| 2021-11-20 00:00:00 | 341.13 | 309.22 | 0.5843 | 0.5368 | 0.5612 | 4.87 | 4.73 | 5.08 | 256.548459 | 253.875275 | 253.761067 | 3.729670 | 3.208010 | 3.932496 | -84.581541 |
| 2021-11-20 00:15:00 | 339.60 | 334.23 | 0.5787 | 0.5445 | 0.5653 | 4.75 | 5.08 | 5.21 | 255.751532 | 246.845170 | 244.925881 | 3.335881 | 3.450055 | 3.918132 | -83.848468 |
| 2021-11-20 00:30:00 | 355.10 | 343.71 | 0.5889 | 0.5494 | 0.5614 | 5.36 | 4.81 | 5.25 | 256.179482 | 247.987775 | 240.254692 | 3.824412 | 3.793800 | 3.866130 | -98.920518 |
| 2021-11-20 00:45:00 | 358.99 | 334.77 | 0.5512 | 0.5456 | 0.5525 | 5.22 | 5.20 | 4.94 | 250.501580 | 253.723330 | 240.381055 | 4.195291 | 3.805244 | 3.857697 | -108.488420 |
| 2021-11-20 01:00:00 | 370.04 | 346.31 | 0.5625 | 0.5382 | 0.5225 | 5.27 | 5.21 | 5.04 | 245.495300 | 250.678891 | 235.531103 | 4.660578 | 4.256435 | 4.361534 | -124.544700 |
Out[1084]:
<seaborn.axisgrid.PairGrid at 0x7fcbf379cb70>
Calculate for each timestamp with meteo parameters the Butterworth KPIs¶
Start with 864 time bins 864 time bins left after removal of time gaps and negative powers True
Out[1087]:
| MER_wave_dir | SEA_wave_dir | MER_wave_height | SEA_wave_height | RTL_wave_height | MER_wave_period | SEA_wave_period | RTL_wave_period | MER_wind_dir | SEA_wind_dir | RTL_wind_dir | MER_wind_speed | SEA_wind_speed | RTL_wind_speed | MER_wind_wave_misalignment | timeseries_test | total_mean_power | total_mean_amplitude_filtered_signal | total_mean_amplitude_filtered_signal_relative | mermaid_mean_power | mermaid_mean_amplitude_filtered_signal | mermaid_mean_amplitude_filtered_signal_relative | seastar_mean_power | seastar_mean_amplitude_filtered_signal | seastar_mean_amplitude_filtered_signal_relative | rentel_mean_power | rentel_mean_amplitude_filtered_signal | rentel_mean_amplitude_filtered_signal_relative | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| datetime | ||||||||||||||||||||||||||||
| 2021-11-20 01:00:00 | 370.04 | 346.31 | 0.5625 | 0.5382 | 0.5225 | 5.27 | 5.21 | 5.04 | 245.495300 | 250.678891 | 235.531103 | 4.660578 | 4.256435 | 4.361534 | -124.544700 | OK | 27.401429 | 0.148253 | 0.541042 | 10.683059 | 0.103825 | 0.971867 | 7.614189 | 0.102180 | 1.341966 | 9.104180 | 0.032468 | 0.356626 |
| 2021-11-20 01:15:00 | 373.36 | 0.06 | 0.5774 | 0.5407 | 0.5385 | 5.45 | 5.06 | 5.35 | 243.957950 | 244.714308 | 228.951270 | 4.823206 | 4.415643 | 4.316449 | -129.402050 | OK | 35.431638 | 0.189511 | 0.534863 | 15.253653 | 0.127520 | 0.835994 | 10.802051 | 0.125245 | 1.159460 | 9.375934 | 0.042503 | 0.453318 |
| 2021-11-20 01:30:00 | 363.05 | 3.48 | 0.5870 | 0.5469 | 0.5605 | 5.35 | 4.92 | 4.94 | 241.902063 | 245.075966 | 228.067144 | 4.673235 | 4.326685 | 4.546509 | -121.147937 | OK | 31.573156 | 0.164152 | 0.519911 | 11.514649 | 0.100068 | 0.869054 | 9.817731 | 0.082966 | 0.845065 | 10.240776 | 0.062650 | 0.611773 |
| 2021-11-20 01:45:00 | 360.04 | 15.21 | 0.5700 | 0.5599 | 0.5600 | 5.70 | 5.25 | 4.90 | 245.206828 | 245.276324 | 221.839254 | 4.959740 | 4.938581 | 5.075320 | -114.833172 | OK | 50.941892 | 0.166187 | 0.326229 | 15.559190 | 0.110261 | 0.708653 | 16.852299 | 0.123511 | 0.732901 | 18.530403 | 0.063269 | 0.341436 |
| 2021-11-20 02:00:00 | 357.57 | 9.69 | 0.5474 | 0.5424 | 0.5666 | 5.63 | 5.24 | 5.00 | 246.191738 | 245.571851 | 222.410997 | 5.168771 | 5.416450 | 5.352771 | -111.378262 | OK | 66.018003 | 0.175710 | 0.266154 | 18.259057 | 0.140418 | 0.769032 | 22.239101 | 0.118280 | 0.531854 | 25.519845 | 0.037834 | 0.148252 |
Can we predict the severity of the tower oscilations with meteo data?¶
Out[1089]:
| MER_wave_dir | SEA_wave_dir | MER_wave_height | SEA_wave_height | RTL_wave_height | MER_wave_period | SEA_wave_period | RTL_wave_period | MER_wind_dir | SEA_wind_dir | RTL_wind_dir | MER_wind_speed | SEA_wind_speed | RTL_wind_speed | MER_wind_wave_misalignment | timeseries_test | total_mean_power | total_mean_amplitude_filtered_signal | total_mean_amplitude_filtered_signal_relative | mermaid_mean_power | mermaid_mean_amplitude_filtered_signal | mermaid_mean_amplitude_filtered_signal_relative | seastar_mean_power | seastar_mean_amplitude_filtered_signal | seastar_mean_amplitude_filtered_signal_relative | rentel_mean_power | rentel_mean_amplitude_filtered_signal | rentel_mean_amplitude_filtered_signal_relative | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| datetime | ||||||||||||||||||||||||||||
| 2021-11-20 01:00:00 | 370.04 | 346.31 | 0.5625 | 0.5382 | 0.5225 | 5.27 | 5.21 | 5.04 | 245.495300 | 250.678891 | 235.531103 | 4.660578 | 4.256435 | 4.361534 | -124.544700 | OK | 27.401429 | 0.148253 | 0.541042 | 10.683059 | 0.103825 | 0.971867 | 7.614189 | 0.102180 | 1.341966 | 9.104180 | 0.032468 | 0.356626 |
| 2021-11-20 01:15:00 | 373.36 | 0.06 | 0.5774 | 0.5407 | 0.5385 | 5.45 | 5.06 | 5.35 | 243.957950 | 244.714308 | 228.951270 | 4.823206 | 4.415643 | 4.316449 | -129.402050 | OK | 35.431638 | 0.189511 | 0.534863 | 15.253653 | 0.127520 | 0.835994 | 10.802051 | 0.125245 | 1.159460 | 9.375934 | 0.042503 | 0.453318 |
| 2021-11-20 01:30:00 | 363.05 | 3.48 | 0.5870 | 0.5469 | 0.5605 | 5.35 | 4.92 | 4.94 | 241.902063 | 245.075966 | 228.067144 | 4.673235 | 4.326685 | 4.546509 | -121.147937 | OK | 31.573156 | 0.164152 | 0.519911 | 11.514649 | 0.100068 | 0.869054 | 9.817731 | 0.082966 | 0.845065 | 10.240776 | 0.062650 | 0.611773 |
| 2021-11-20 01:45:00 | 360.04 | 15.21 | 0.5700 | 0.5599 | 0.5600 | 5.70 | 5.25 | 4.90 | 245.206828 | 245.276324 | 221.839254 | 4.959740 | 4.938581 | 5.075320 | -114.833172 | OK | 50.941892 | 0.166187 | 0.326229 | 15.559190 | 0.110261 | 0.708653 | 16.852299 | 0.123511 | 0.732901 | 18.530403 | 0.063269 | 0.341436 |
| 2021-11-20 02:00:00 | 357.57 | 9.69 | 0.5474 | 0.5424 | 0.5666 | 5.63 | 5.24 | 5.00 | 246.191738 | 245.571851 | 222.410997 | 5.168771 | 5.416450 | 5.352771 | -111.378262 | OK | 66.018003 | 0.175710 | 0.266154 | 18.259057 | 0.140418 | 0.769032 | 22.239101 | 0.118280 | 0.531854 | 25.519845 | 0.037834 | 0.148252 |
Out[1090]:
<seaborn.axisgrid.PairGrid at 0x7fcbf31644a8>
Selected features: ['MER_wave_dir', 'MER_wave_height', 'MER_wave_period', 'MER_wind_dir', 'MER_wind_speed', 'MER_wind_wave_misalignment']
Out[1092]:
<matplotlib.legend.Legend at 0x7fcbf7a84080>
Out[1096]:
Text(69.0, 0.5, 'Wave height [m]')
End of notebook. From here old code¶
Read in old meteo files¶
Read in lidar meteo files¶
Out[877]:
| wave_dir_MER | wave_dir_SEA | |
|---|---|---|
| datetime | ||
| 2/11/2021 0:00 | 217.12 | 226.62 |
| 2/11/2021 0:15 | 214.99 | 230.22 |
| 2/11/2021 0:30 | 212.14 | 230.47 |
| 2/11/2021 0:45 | 211.57 | 226.92 |
| 2/11/2021 1:00 | 217.40 | 230.94 |
Out[876]:
<matplotlib.axes._subplots.AxesSubplot at 0x7fcba5f06cf8>
Old Code¶
Out[119]:
{'start_time': Timestamp('2021-11-13 16:47:33'),
'stop_time': Timestamp('2021-11-13 16:52:32'),
'timeseries_test': 'OK',
'total_park_power_negative_test': 'OK',
'mermaid_park_power_negative_test': 'OK',
'mermaid_filtered_signal_average_amplitude': 0.24254927841919197,
'mermaid_max_power': 118.736,
'mermaid_average_power': 111.98593266666673,
'mermaid_min_power': 103.6371,
'mermaid_amplitude': 0.1667630224324502,
'mermaid_amplitude_rel': 0.14891425955153756,
'mermaid_resonance_frequency': 0.23333333333333334,
'seastar_park_power_negative_test': 'OK',
'seastar_filtered_signal_average_amplitude': 0.18598199170164342,
'seastar_max_power': 62.81275,
'seastar_average_power': 59.73935816666667,
'seastar_min_power': 54.37234,
'seastar_amplitude': 0.14249051333369636,
'seastar_amplitude_rel': 0.23852032848455196,
'seastar_resonance_frequency': 0.23333333333333334,
'rentel_park_power_negative_test': 'OK',
'rentel_filtered_signal_average_amplitude': 0.043373725120614395,
'rentel_max_power': 65.22646,
'rentel_average_power': 61.69941126666666,
'rentel_min_power': 58.20838,
'rentel_amplitude': 0.044277295076644005,
'rentel_amplitude_rel': 0.07176291340167938,
'rentel_resonance_frequency': 0.25333333333333335,
'total_filtered_signal_average_amplitude': 0.36033703636948433,
'total_max_power': 241.38230000000001,
'total_average_power': 233.42470209999993,
'total_min_power': 222.45371,
'total_amplitude': 0.29316758545100957,
'total_amplitude_rel': 0.12559407072753404,
'total_resonance_frequency': 0.23333333333333334}
Fourier parameters for the complete period¶
Calculate the frequency parameters of a random 1000 40seconds bins¶
Calculating parameters of random window 0 Calculating parameters of random window 10 Calculating parameters of random window 20 Calculating parameters of random window 30 Calculating parameters of random window 40 Calculating parameters of random window 50 Calculating parameters of random window 60 Calculating parameters of random window 70 Calculating parameters of random window 80 Calculating parameters of random window 90 Calculating parameters of random window 100 Calculating parameters of random window 110 Calculating parameters of random window 120 Calculating parameters of random window 130 Calculating parameters of random window 140 Calculating parameters of random window 150 Calculating parameters of random window 160 Calculating parameters of random window 170 Calculating parameters of random window 180 Calculating parameters of random window 190 Calculating parameters of random window 200 Calculating parameters of random window 210 Calculating parameters of random window 220 Calculating parameters of random window 230 Calculating parameters of random window 240 Calculating parameters of random window 250 Calculating parameters of random window 260 Calculating parameters of random window 270 Calculating parameters of random window 280 Calculating parameters of random window 290 Calculating parameters of random window 300 Calculating parameters of random window 310 Calculating parameters of random window 320 Calculating parameters of random window 330 Calculating parameters of random window 340 Calculating parameters of random window 350 Calculating parameters of random window 360 Calculating parameters of random window 370 Calculating parameters of random window 380 Calculating parameters of random window 390 Calculating parameters of random window 400 Calculating parameters of random window 410 Calculating parameters of random window 420 Calculating parameters of random window 430 Calculating parameters of random window 440 Calculating parameters of random window 450 Calculating parameters of random window 460 Calculating parameters of random window 470 Calculating parameters of random window 480 Calculating parameters of random window 490 Calculating parameters of random window 500 Calculating parameters of random window 510 Calculating parameters of random window 520 Calculating parameters of random window 530 Calculating parameters of random window 540 Calculating parameters of random window 550 Calculating parameters of random window 560 Calculating parameters of random window 570 Calculating parameters of random window 580 Calculating parameters of random window 590 Calculating parameters of random window 600 Calculating parameters of random window 610 Calculating parameters of random window 620 Calculating parameters of random window 630 Calculating parameters of random window 640 Calculating parameters of random window 650 Calculating parameters of random window 660 Calculating parameters of random window 670 Calculating parameters of random window 680 Calculating parameters of random window 690 Calculating parameters of random window 700 Calculating parameters of random window 710 Calculating parameters of random window 720 Calculating parameters of random window 730 Calculating parameters of random window 740 Calculating parameters of random window 750 Calculating parameters of random window 760 Calculating parameters of random window 770 Calculating parameters of random window 780 Calculating parameters of random window 790 Calculating parameters of random window 800 Calculating parameters of random window 810 Calculating parameters of random window 820 Calculating parameters of random window 830 Calculating parameters of random window 840 Calculating parameters of random window 850 Calculating parameters of random window 860 Calculating parameters of random window 870 Calculating parameters of random window 880 Calculating parameters of random window 890 Calculating parameters of random window 900 Calculating parameters of random window 910 Calculating parameters of random window 920 Calculating parameters of random window 930 Calculating parameters of random window 940 Calculating parameters of random window 950 Calculating parameters of random window 960 Calculating parameters of random window 970 Calculating parameters of random window 980 Calculating parameters of random window 990
OK 858 Len TS 300.0 not equal to number of seconds 298.0 5 Len TS 300.0 not equal to number of seconds 296.0 3 Name: timeseries_test, dtype: int64
Out[123]:
| start_time | stop_time | timeseries_test | total_park_power_negative_test | mermaid_park_power_negative_test | mermaid_filtered_signal_average_amplitude | mermaid_max_power | mermaid_average_power | mermaid_min_power | mermaid_amplitude | mermaid_amplitude_rel | mermaid_resonance_frequency | seastar_park_power_negative_test | seastar_filtered_signal_average_amplitude | seastar_max_power | seastar_average_power | seastar_min_power | seastar_amplitude | seastar_amplitude_rel | seastar_resonance_frequency | rentel_park_power_negative_test | rentel_filtered_signal_average_amplitude | rentel_max_power | rentel_average_power | rentel_min_power | rentel_amplitude | rentel_amplitude_rel | rentel_resonance_frequency | total_filtered_signal_average_amplitude | total_max_power | total_average_power | total_min_power | total_amplitude | total_amplitude_rel | total_resonance_frequency | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2021-11-23 12:21:10 | 2021-11-23 12:26:09 | OK | OK | OK | 0.248804 | 28.838310 | 26.911952 | 24.667610 | 0.208970 | 0.776495 | 0.236667 | OK | 0.209502 | 27.05401 | 23.760286 | 21.18962 | 0.189642 | 0.798147 | 0.233333 | OK | 0.025446 | 25.438870 | 23.747441 | 22.137500 | 0.011101 | 0.046745 | 0.180000 | 0.306592 | 79.216750 | 74.419680 | 70.034230 | 0.206572 | 0.277577 | 0.233333 |
| 1 | 2021-11-06 07:29:14 | 2021-11-06 07:34:13 | OK | OK | OK | 0.385960 | 198.168700 | 190.850436 | 184.666100 | 0.312437 | 0.163708 | 0.233333 | OK | 0.262667 | 232.28680 | 227.184274 | 220.39280 | 0.196709 | 0.086586 | 0.240000 | OK | 0.218588 | 269.890600 | 264.791845 | 260.153400 | 0.175334 | 0.066216 | 0.250000 | 0.487668 | 692.750800 | 682.826555 | 670.253400 | 0.372427 | 0.054542 | 0.233333 |
| 2 | 2021-11-04 17:49:15 | 2021-11-04 17:54:14 | OK | OK | OK | 0.285256 | 221.613800 | 219.841059 | 218.348200 | 0.179621 | 0.081705 | 0.220000 | OK | 0.333145 | 221.96730 | 216.604455 | 208.84140 | 0.377428 | 0.174248 | 0.236667 | OK | 0.218239 | 226.153000 | 203.112015 | 187.161300 | 0.174873 | 0.086097 | 0.256667 | 0.441640 | 665.051100 | 639.557529 | 621.603000 | 0.345952 | 0.054092 | 0.236667 |
| 3 | 2021-11-10 23:55:07 | 2021-11-11 00:00:06 | OK | OK | OK | 0.055926 | 3.755295 | 2.072404 | 1.007462 | 0.035316 | 1.704092 | 0.230000 | OK | 0.078943 | 14.17403 | 12.814087 | 11.40289 | 0.076213 | 0.594760 | 0.236667 | OK | 0.066729 | 9.629824 | 8.682863 | 7.745285 | 0.035976 | 0.414332 | 0.256667 | 0.117933 | 26.276589 | 23.569354 | 20.995204 | 0.086692 | 0.367817 | 0.236667 |
| 4 | 2021-11-08 03:58:05 | 2021-11-08 04:03:04 | OK | OK | OK | 0.388793 | 55.525460 | 50.703790 | 45.745200 | 0.347646 | 0.685642 | 0.240000 | OK | 0.379272 | 24.05569 | 21.431527 | 19.34124 | 0.253738 | 1.183949 | 0.236667 | OK | 0.054654 | 20.892550 | 19.009387 | 15.771830 | 0.032463 | 0.170774 | 0.246667 | 0.473719 | 96.336490 | 91.144704 | 83.566200 | 0.448196 | 0.491741 | 0.233333 |
